Image compression is an essential element of many digital imaging systems due to the vast amount of information contained in a digitized image. Because of its simplicity, compression efficiency and ease of implementation, linear predictive coding (LPC) is often used to compress image data for storage and transmission. LPC refers to the general class of coding techniques in which the difference or error between a given signal value and a linear prediction of the signal value, based on correlated signal values, is coded. The advantage of coding the error signal is that it is less correlated, has lower variance, and is more stationary than the original signal, which make it easier to compress.
Depending on the type of image and the level of adaptability to variations in image structure, compression ratios from 2:1 to 6:1 have been achieved. Both adaptive prediction (see, for example, "DPCM Picture Coding with Adaptive Prediction" by Zschunke, IEEE Transaction on Communications, Vol. Com-25, November, 1977, pages 1295-1302), and adaptive quantization (see, for example, "Adaptive Predictive Coding with Applications to Radiographs" by M. Rabbani, L. A. Ray, and J. Sullivan, Medical Instrumentation, Vol. 20, No. 4, July-August, 1986, pages 182-191) have been examined, with most of the emphasis being placed on adaptive quantization due to its superior performance for a given hardware implementation complexity.
The predominant adaptive quantization technique is termed block-adaptive wherein a quantizer is selected from a finite set of quantizers to encode a one-dimensional block of error signals based on the statistics of independent one-dimensional blocks. A number of empirical studies have been conducted to establish the best set of single-variable quantizers (see, for example, "On the Design of Quantizers for DPCM Coders: A Functional Relationship Between Visibility, Probability, and Masking" by J. O. Limb and C. B. Rubinstein, IEEE Transactions on Communications Techniques, COM-26, 1978, pages 573-578) and multi-variable quantizers (see, for example, "A New ADPCM Image Compression Algorithm and the Effect of Fixed-Pattern Sensor Noise" by J. Sullivan, SPIE Vol 1075, 1989, pages 129-138, and U.S. Pat. No. 4,885,636 entitled "Block Adaptive Linear Productive Coding with Adaptive Gain and Bias," issued Dec. 5, 1989 to the present inventor, which is incorporated herein by reference). All of these studies have concerned variations in the quantizer based on one-dimensional block-to-block variations of the error signal statistics. It is an object of the present invention to provide a new block adaptive LPC technique that improves the compression ratio over the aforementioned techniques for a given image fidelity for all classes of images of interest to a human observer, thereby reducing storage requirements and/or transmission times.